6 citations · 21 across the 11 of their papers we have counts for
11 papers
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning
Taehoon Kim, Pyunghwan Ahn, Sangyun Kim +39
In this report, we introduce NICE (New frontiers for zero-shot Image Captioning Evaluation) project and share the results and outcomes of 2023 challenge. This project is designed t…
Self-Sufficient Framework for Continuous Sign Language Recognition
Youngjoon Jang, Youngtaek Oh, Jae Won Cho +4
The goal of this work is to develop self-sufficient framework for Continuous Sign Language Recognition (CSLR) that addresses key issues of sign language recognition. These include…
Signing Outside the Studio: Benchmarking Background Robustness for Continuous Sign Language Recognition
Youngjoon Jang, Youngtaek Oh, Jae Won Cho +3
The goal of this work is background-robust continuous sign language recognition. Most existing Continuous Sign Language Recognition (CSLR) benchmarks have fixed backgrounds and are…
Generative Bias for Robust Visual Question Answering
Jae Won Cho, Dong-jin Kim, Hyeonggon Ryu +1
The task of Visual Question Answering (VQA) is known to be plagued by the issue of VQA models exploiting biases within the dataset to make its final prediction. Various previous en…
Investigating Top- White-Box and Transferable Black-box Attack
Chaoning Zhang, Philipp Benz, Adil Karjauv +3
Existing works have identified the limitation of top- attack success rate (ASR) as a metric to evaluate the attack strength but exclusively investigated it in the white-box sett…
Single-Modal Entropy based Active Learning for Visual Question Answering
Dong-Jin Kim, Jae Won Cho, Jinsoo Choi +2
Constructing a large-scale labeled dataset in the real world, especially for high-level tasks (eg, Visual Question Answering), can be expensive and time-consuming. In addition, wit…
Correlate-and-Excite: Real-Time Stereo Matching via Guided Cost Volume Excitation
Antyanta Bangunharcana, Jae Won Cho, Seokju Lee +3
Volumetric deep learning approach towards stereo matching aggregates a cost volume computed from input left and right images using 3D convolutions. Recent works showed that utiliza…
LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation
Inkyu Shin, Dong-jin Kim, Jae Won Cho +3
Unsupervised Domain Adaptation (UDA) for semantic segmentation has been actively studied to mitigate the domain gap between label-rich source data and unlabeled target data. Despit…
MCDAL: Maximum Classifier Discrepancy for Active Learning
Jae Won Cho, Dong-Jin Kim, Yunjae Jung +1
Recent state-of-the-art active learning methods have mostly leveraged Generative Adversarial Networks (GAN) for sample acquisition; however, GAN is usually known to suffer from ins…
Dealing with Missing Modalities in the Visual Question Answer-Difference Prediction Task through Knowledge Distillation
Jae Won Cho, Dong-Jin Kim, Jinsoo Choi +2
In this work, we address the issues of missing modalities that have arisen from the Visual Question Answer-Difference prediction task and find a novel method to solve the task at h…
Optical Flow Estimation from a Single Motion-blurred Image
Dawit Mureja Argaw, Junsik Kim, Francois Rameau +2
In most of computer vision applications, motion blur is regarded as an undesirable artifact. However, it has been shown that motion blur in an image may have practical interests in…